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<div class="title">neon_copy_objects.cpp</div>  </div>
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<a href="neon__copy__objects_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2016, 2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_n_e_functions_8h.xhtml">arm_compute/runtime/NEON/NEFunctions.h</a>&quot;</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="arm__compute_2core_2_types_8h.xhtml">arm_compute/core/Types.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="utils_2_utils_8h.xhtml">utils/Utils.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#include &lt;cstring&gt;</span></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#include &lt;iostream&gt;</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;</div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute.xhtml">arm_compute</a>;</div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;<span class="keyword">using namespace </span>utils;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;</div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;<span class="keyword">class </span>NEONCopyObjectsExample : <span class="keyword">public</span> <a class="code" href="classarm__compute_1_1utils_1_1_example.xhtml">Example</a></div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;{</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;<span class="keyword">public</span>:</div><div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;    <span class="keywordtype">void</span> do_setup(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span> **argv)<span class="keyword"> override</span></div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="keyword">    </span>{</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;        <a class="code" href="core_2_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(argc);</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;        <a class="code" href="core_2_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a>(argv);</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;        constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> width  = 4;</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;        constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> height = 3;</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;        constexpr <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> batch  = 2;</div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;</div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;        src_data = <span class="keyword">new</span> <span class="keywordtype">float</span>[width * height * batch];</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;        dst_data = <span class="keyword">new</span> <span class="keywordtype">float</span>[width * height * batch];</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;        <span class="comment">// Fill src_data with dummy values:</span></div><div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">b</a> = 0; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">b</a> &lt; batch; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">b</a>++)</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;        {</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;            <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> h = 0; h &lt; height; h++)</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;            {</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;                <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> w = 0; w &lt; width; w++)</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;                {</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;                    src_data[<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">b</a> * (width * height) + h * width + w] = static_cast&lt;float&gt;(100 * <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">b</a> + 10 * h + w);</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;                }</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;            }</div><div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;        }</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;        <span class="comment">// Initialize the tensors dimensions and type:</span></div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;        <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>(width, height, batch);</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        input.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        output.allocator()-&gt;init(<a class="code" href="classarm__compute_1_1_tensor_info.xhtml">TensorInfo</a>(<a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>));</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        <span class="comment">// Configure softmax:</span></div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;        softmax.configure(&amp;input, &amp;output);</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;        <span class="comment">// Allocate the input / output tensors:</span></div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;        input.allocator()-&gt;allocate();</div><div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;        output.allocator()-&gt;allocate();</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;        <span class="comment">// Fill the input tensor:</span></div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;        <span class="comment">// Simplest way: create an iterator to iterate through each element of the input tensor:</span></div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> input_window;</div><div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;        input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(input.info()-&gt;tensor_shape());</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; Dimensions of the input&#39;s iterator:\n&quot;</span>;</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; X = [start=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#ade63ce331b49eb66d330aab444e57ca9">x</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#a27c3790df96e9523b0370e7e10c0d375">start</a>() &lt;&lt; <span class="stringliteral">&quot;, end=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#ade63ce331b49eb66d330aab444e57ca9">x</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#aa9a8509af319b9e47f00c8fba23d368b">end</a>() &lt;&lt; <span class="stringliteral">&quot;, step=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#ade63ce331b49eb66d330aab444e57ca9">x</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#a992b375fc3254afe2e38f63bc29a43d4">step</a>() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; Y = [start=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#aedd49c804f269c0e2c251c4efd44a275">y</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#a27c3790df96e9523b0370e7e10c0d375">start</a>() &lt;&lt; <span class="stringliteral">&quot;, end=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#aedd49c804f269c0e2c251c4efd44a275">y</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#aa9a8509af319b9e47f00c8fba23d368b">end</a>() &lt;&lt; <span class="stringliteral">&quot;, step=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#aedd49c804f269c0e2c251c4efd44a275">y</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#a992b375fc3254afe2e38f63bc29a43d4">step</a>() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; Z = [start=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#ade6a04ff1f61b38e07ddb8ef741c996b">z</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#a27c3790df96e9523b0370e7e10c0d375">start</a>() &lt;&lt; <span class="stringliteral">&quot;, end=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#ade6a04ff1f61b38e07ddb8ef741c996b">z</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#aa9a8509af319b9e47f00c8fba23d368b">end</a>() &lt;&lt; <span class="stringliteral">&quot;, step=&quot;</span> &lt;&lt; input_window.<a class="code" href="classarm__compute_1_1_window.xhtml#ade6a04ff1f61b38e07ddb8ef741c996b">z</a>().<a class="code" href="classarm__compute_1_1_window_1_1_dimension.xhtml#a992b375fc3254afe2e38f63bc29a43d4">step</a>() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;        <span class="comment">// Create an iterator:</span></div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;        <a class="code" href="classarm__compute_1_1_iterator.xhtml">Iterator</a> input_it(&amp;input, input_window);</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;        <span class="comment">// Iterate through the elements of src_data and copy them one by one to the input tensor:</span></div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;        <span class="comment">// This is equivalent to:</span></div><div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;        <span class="comment">// for( unsigned int z = 0; z &lt; batch; ++z)</span></div><div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;        <span class="comment">// {</span></div><div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;        <span class="comment">//   for( unsigned int y = 0; y &lt; height; ++y)</span></div><div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;        <span class="comment">//   {</span></div><div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;        <span class="comment">//     for( unsigned int x = 0; x &lt; width; ++x)</span></div><div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;        <span class="comment">//     {</span></div><div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;        <span class="comment">//       *reinterpret_cast&lt;float*&gt;( input.buffer() + input.info()-&gt;offset_element_in_bytes(Coordinates(x,y,z))) = src_data[ z * (width*height) + y * width + x];</span></div><div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        <span class="comment">//     }</span></div><div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;        <span class="comment">//   }</span></div><div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;        <span class="comment">// }</span></div><div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;        <span class="comment">// Except it works for an arbitrary number of dimensions</span></div><div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(input_window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div><div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;        {</div><div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Setting item [&quot;</span> &lt;&lt; <span class="keywordtype">id</span>.<a class="code" href="classarm__compute_1_1_window.xhtml#ade63ce331b49eb66d330aab444e57ca9">x</a>() &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; <span class="keywordtype">id</span>.y() &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; <span class="keywordtype">id</span>.z() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;            *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(input_it.ptr()) = src_data[<span class="keywordtype">id</span>.z() * (width * height) + <span class="keywordtype">id</span>.y() * width + <span class="keywordtype">id</span>.x()];</div><div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;        },</div><div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        input_it);</div><div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;</div><div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;        <span class="comment">// More efficient way: create an iterator to iterate through each row (instead of each element) of the output tensor:</span></div><div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;        <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> output_window;</div><div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;        output_window.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(output.info()-&gt;tensor_shape(), <span class="comment">/* first_dimension =*/</span><a class="code" href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">Window::DimY</a>); <span class="comment">// Iterate through the rows (not each element)</span></div><div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; Dimensions of the output&#39;s iterator:\n&quot;</span>;</div><div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; X = [start=&quot;</span> &lt;&lt; output_window.x().start() &lt;&lt; <span class="stringliteral">&quot;, end=&quot;</span> &lt;&lt; output_window.x().end() &lt;&lt; <span class="stringliteral">&quot;, step=&quot;</span> &lt;&lt; output_window.x().step() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; Y = [start=&quot;</span> &lt;&lt; output_window.y().start() &lt;&lt; <span class="stringliteral">&quot;, end=&quot;</span> &lt;&lt; output_window.y().end() &lt;&lt; <span class="stringliteral">&quot;, step=&quot;</span> &lt;&lt; output_window.y().step() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;        std::cout &lt;&lt; <span class="stringliteral">&quot; Z = [start=&quot;</span> &lt;&lt; output_window.z().start() &lt;&lt; <span class="stringliteral">&quot;, end=&quot;</span> &lt;&lt; output_window.z().end() &lt;&lt; <span class="stringliteral">&quot;, step=&quot;</span> &lt;&lt; output_window.z().step() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;</div><div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;        <span class="comment">// Create an iterator:</span></div><div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;        <a class="code" href="classarm__compute_1_1_iterator.xhtml">Iterator</a> output_it(&amp;output, output_window);</div><div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;</div><div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;        <span class="comment">// Iterate through the rows of the output tensor and copy them to dst_data:</span></div><div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;        <span class="comment">// This is equivalent to:</span></div><div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;        <span class="comment">// for( unsigned int z = 0; z &lt; batch; ++z)</span></div><div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;        <span class="comment">// {</span></div><div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;        <span class="comment">//   for( unsigned int y = 0; y &lt; height; ++y)</span></div><div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;        <span class="comment">//   {</span></div><div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;        <span class="comment">//     memcpy( dst_data + z * (width*height) + y * width, input.buffer() + input.info()-&gt;offset_element_in_bytes(Coordinates(0,y,z)), width * sizeof(float));</span></div><div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;        <span class="comment">//   }</span></div><div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        <span class="comment">// }</span></div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;        <span class="comment">// Except it works for an arbitrary number of dimensions</span></div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(output_window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div><div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;        {</div><div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;            std::cout &lt;&lt; <span class="stringliteral">&quot;Copying one row starting from [&quot;</span> &lt;&lt; <span class="keywordtype">id</span>.x() &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; <span class="keywordtype">id</span>.y() &lt;&lt; <span class="stringliteral">&quot;,&quot;</span> &lt;&lt; <span class="keywordtype">id</span>.z() &lt;&lt; <span class="stringliteral">&quot;]\n&quot;</span>;</div><div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;            <span class="comment">// Copy one whole row:</span></div><div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;            memcpy(dst_data + <span class="keywordtype">id</span>.z() * (width * height) + <span class="keywordtype">id</span>.y() * width, output_it.ptr(), width * <span class="keyword">sizeof</span>(float));</div><div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;        },</div><div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;        output_it);</div><div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;</div><div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;    }</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;    <span class="keywordtype">void</span> do_run()<span class="keyword"> override</span></div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;<span class="keyword">    </span>{</div><div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;        <span class="comment">// Run NEON softmax:</span></div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;        softmax.run();</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;    }</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    <span class="keywordtype">void</span> do_teardown()<span class="keyword"> override</span></div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;<span class="keyword">    </span>{</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;        <span class="keyword">delete</span>[] src_data;</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;        <span class="keyword">delete</span>[] dst_data;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    }</div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;<span class="keyword">private</span>:</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    <a class="code" href="classarm__compute_1_1_tensor.xhtml">Tensor</a>         input{}, output{};</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;    <span class="keywordtype">float</span>         *src_data{};</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    <span class="keywordtype">float</span>         *dst_data{};</div><div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;    <a class="code" href="classarm__compute_1_1_n_e_softmax_layer.xhtml">NESoftmaxLayer</a> softmax{};</div><div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;};</div><div class="line"><a name="l00161"></a><span class="lineno"><a class="line" href="neon__copy__objects_8cpp.xhtml#a3c04138a5bfe5d72780bb7e82a18e627">  161</a></span>&#160;<span class="keywordtype">int</span> <a class="code" href="neon__copy__objects_8cpp.xhtml#a3c04138a5bfe5d72780bb7e82a18e627">main</a>(<span class="keywordtype">int</span> argc, <span class="keywordtype">char</span> **argv)</div><div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;{</div><div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    <span class="keywordflow">return</span> utils::run_example&lt;NEONCopyObjectsExample&gt;(argc, argv);</div><div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;}</div><div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00133">Convolution.cpp:133</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="utils_2_utils_8h_xhtml"><div class="ttname"><a href="utils_2_utils_8h.xhtml">Utils.h</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1_window_1_1_dimension_xhtml_a27c3790df96e9523b0370e7e10c0d375"><div class="ttname"><a href="classarm__compute_1_1_window_1_1_dimension.xhtml#a27c3790df96e9523b0370e7e10c0d375">arm_compute::Window::Dimension::start</a></div><div class="ttdeci">constexpr int start() const </div><div class="ttdoc">Return the start of the dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00085">Window.h:85</a></div></div>
<div class="ttc" id="core_2_error_8h_xhtml_a4103adbb45806b2f2002d44b91d0d206"><div class="ttname"><a href="core_2_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(var)</div><div class="ttdoc">To avoid unused variables warnings. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00147">Error.h:147</a></div></div>
<div class="ttc" id="classarm__compute_1_1_n_e_softmax_layer_xhtml"><div class="ttname"><a href="classarm__compute_1_1_n_e_softmax_layer.xhtml">arm_compute::NESoftmaxLayer</a></div><div class="ttdoc">Basic function to compute a SoftmaxLayer. </div><div class="ttdef"><b>Definition:</b> <a href="_n_e_softmax_layer_8h_source.xhtml#l00047">NESoftmaxLayer.h:47</a></div></div>
<div class="ttc" id="_n_e_functions_8h_xhtml"><div class="ttname"><a href="_n_e_functions_8h.xhtml">NEFunctions.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_a14470b4cb59140a1b6ff3b8f16c89ab6"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">arm_compute::Window::use_tensor_dimensions</a></div><div class="ttdeci">void use_tensor_dimensions(const TensorShape &amp;shape, size_t first_dimension=Window::DimX)</div><div class="ttdoc">Use the tensor&amp;#39;s dimensions to fill the window dimensions. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00240">Window.inl:240</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml"><div class="ttname"><a href="namespacearm__compute.xhtml">arm_compute</a></div><div class="ttdoc">This file contains all available output stages for GEMMLowp on OpenCL. </div><div class="ttdef"><b>Definition:</b> <a href="00__introduction_8dox_source.xhtml#l00001">00_introduction.dox:1</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_1_1_dimension_xhtml_aa9a8509af319b9e47f00c8fba23d368b"><div class="ttname"><a href="classarm__compute_1_1_window_1_1_dimension.xhtml#aa9a8509af319b9e47f00c8fba23d368b">arm_compute::Window::Dimension::end</a></div><div class="ttdeci">constexpr int end() const </div><div class="ttdoc">Return the end of the dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00090">Window.h:90</a></div></div>
<div class="ttc" id="neon__copy__objects_8cpp_xhtml_a3c04138a5bfe5d72780bb7e82a18e627"><div class="ttname"><a href="neon__copy__objects_8cpp.xhtml#a3c04138a5bfe5d72780bb7e82a18e627">main</a></div><div class="ttdeci">int main(int argc, char **argv)</div><div class="ttdoc">Main program for the copy objects test. </div><div class="ttdef"><b>Definition:</b> <a href="neon__copy__objects_8cpp_source.xhtml#l00161">neon_copy_objects.cpp:161</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_aedd49c804f269c0e2c251c4efd44a275"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#aedd49c804f269c0e2c251c4efd44a275">arm_compute::Window::y</a></div><div class="ttdeci">constexpr const Dimension &amp; y() const </div><div class="ttdoc">Alias to access the second dimension of the window. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00145">Window.h:145</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a6c0dcc38187027dcb89cd9724bc5a823"><div class="ttname"><a href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">arm_compute::execute_window_loop</a></div><div class="ttdeci">void execute_window_loop(const Window &amp;w, L &amp;&amp;lambda_function, Ts &amp;&amp;...iterators)</div><div class="ttdoc">Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00122">Helpers.inl:122</a></div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item. </div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1utils_1_1_example_xhtml"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_example.xhtml">arm_compute::utils::Example</a></div><div class="ttdoc">Abstract Example class. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00062">Utils.h:62</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor.xhtml">arm_compute::Tensor</a></div><div class="ttdoc">Basic implementation of the tensor interface. </div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_tensor_8h_source.xhtml#l00037">Tensor.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_ad2d402364fa822b0b7775081291eeca9"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ad2d402364fa822b0b7775081291eeca9">arm_compute::Window::DimY</a></div><div class="ttdeci">static constexpr size_t DimY</div><div class="ttdoc">Alias for dimension 1 also known as Y dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00045">Window.h:45</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_1_1_dimension_xhtml_a992b375fc3254afe2e38f63bc29a43d4"><div class="ttname"><a href="classarm__compute_1_1_window_1_1_dimension.xhtml#a992b375fc3254afe2e38f63bc29a43d4">arm_compute::Window::Dimension::step</a></div><div class="ttdeci">constexpr int step() const </div><div class="ttdoc">Return the step of the dimension. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00095">Window.h:95</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_info_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_info.xhtml">arm_compute::TensorInfo</a></div><div class="ttdoc">Store the tensor&amp;#39;s metadata. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_info_8h_source.xhtml#l00044">TensorInfo.h:44</a></div></div>
<div class="ttc" id="classarm__compute_1_1_iterator_xhtml"><div class="ttname"><a href="classarm__compute_1_1_iterator.xhtml">arm_compute::Iterator</a></div><div class="ttdoc">Iterator updated by execute_window_loop for each window element. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_helpers_8h_source.xhtml#l00257">Helpers.h:257</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7b8004eef325a40dd43eb80755610fff"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">arm_compute::test::validation::b</a></div><div class="ttdeci">CLTensor b</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_g_e_m_m_8cpp_source.xhtml#l00122">GEMM.cpp:122</a></div></div>
<div class="ttc" id="arm__compute_2core_2_types_8h_xhtml"><div class="ttname"><a href="arm__compute_2core_2_types_8h.xhtml">Types.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_ade6a04ff1f61b38e07ddb8ef741c996b"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ade6a04ff1f61b38e07ddb8ef741c996b">arm_compute::Window::z</a></div><div class="ttdeci">constexpr const Dimension &amp; z() const </div><div class="ttdoc">Alias to access the third dimension of the window. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00154">Window.h:154</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_ade63ce331b49eb66d330aab444e57ca9"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#ade63ce331b49eb66d330aab444e57ca9">arm_compute::Window::x</a></div><div class="ttdeci">constexpr const Dimension &amp; x() const </div><div class="ttdoc">Alias to access the first dimension of the window. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00136">Window.h:136</a></div></div>
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